Radiation therapy, also known as radiotherapy, is used to treat tumors and other ailments in mammalian (e.g., human and animal) tissue. An example of a radiotherapy treatment would be the application of a high-energy beam from an external source towards a patient to produce a collimated beam of radiation directed to a target site of a patient. The target may be a region of the patient's body that contains a diseased organ or tumor that is to be exposed to, and treated by, the radiation beam. The placement and dose of the radiation beam must be accurately controlled to ensure that the target receives the dose of radiation that has been prescribed for the patient by a physician yet damage to the surrounding healthy tissue, often called the organ(s) at risk (OARs), is minimized.
To plan a patient's radiotherapy treatment one or more medical images of the patient in the intended treatment position are acquired prior to a radiation therapy treatment session and are often acquired many days before the initiation of treatment. These are referred to as planning images.
Physicians can use the planning images to identify and contour a target or targets as well as OARs. Contouring can be performed manually, semi-automatically, or automatically. A treatment contour, often referred to as a planned target volume (PTV), is created which includes the target contour plus sufficient margins to account for microscopic disease as well as treatment uncertainties. A radiation dose is prescribed by the physician, and a radiation therapy treatment plan is created that optimally delivers the prescribed dose to the PTV while minimizing dose to the OARs and other normal tissues. The treatment plan can be generated manually by the physician, or can be generated automatically using an optimization technique. The optimization technique may be based on clinical and dosimetric objectives and constraints (e.g., the maximum, minimum, and mean doses of radiation to the tumor and OARs).
A treatment course is developed to deliver the prescribed dose over a number of fractions, wherein each fraction is delivered in a different treatment session. For example, 30-40 fractions are typical, but five or even one fraction can be used. Fractions are typically delivered once, or in some cases twice, per weekday. In some cases, the radiation treatment plan can change throughout the course to focus more dose in some areas.
At each fraction, the patient is set up on a patient support accessory (often referred to as the “couch”) of a radiation therapy device, and repositioned as closely as possible to their position in the planning images. Unfortunately, this is a difficult task to carry out accurately in practice, because the patient is not a rigid object and the patient's anatomy can move or change. Fraction-to-fraction variations or changes are often referred to as interfractional variations, while variation or changes occurring during a fraction itself are often referred to as intrafractional variations.
Image-guided radiotherapy (IGRT) attempts to minimize the problem of interfractional variation. IGRT involves acquiring one or more medical images of the patient shortly before radiation therapy, and using those images to identify and compensate for interfractional variation. As opposed to planning images, which can be acquired on any diagnostic scanner, IGRT images are acquired directly in the treatment room, while the patient is in the treatment position. To compensate for interfractional variation, IGRT images are compared with the planning images to quantify changes in the patient's anatomy that have occurred since the planning images were generated. For example, the planning images and IGRT images may be analyzed to calculate a global shift and/or rotation that best aligns the planning images to the IGRT images. Once the shift and/or rotation have been calculated, a corresponding adjustment to the position of the patient support accessory can be made, such that the position of the patient during the treatment session more closely matches the position of the patient when the planning images were acquired. Note that in this scenario, the original plan is still delivered, and only the patient's position has been changed to minimize the deviation from what was planned.
Adaptive radiotherapy is another technique that aims to solve the problem of interfractional variation. As with IGRT, adaptive radiotherapy involves acquiring one or more medical images of the patient shortly before a radiation therapy treatment session, and using those images to identify and compensate for interfractional variation. However, in adaptive radiotherapy, not only may the patient's position be changed, but the plan itself may be adapted to account for interfractional variations. In adaptive radiotherapy, the planning images and the images taken shortly before the treatment session may be analyzed to generate a deformation vector field (DVF). The DVF is a 3D array whose elements are vectors, and in which each vector defines a geometric transformation to map a voxel in a planning image to the corresponding voxel in an image taken shortly before the treatment session. This DVF can be used to transform the spatial distribution of the radiation dose prescribed in the original treatment plan, in order to account for changes in the patient's anatomy that have occurred since the planning images were acquired. This transformed dose distribution results in a dose distribution that is equivalent to the approved dose distribution from the original, approved treatment plan and may be used as a “goal” dose for a replanning activity, with the idea being if one can find a plan that achieves this transformed dose distribution, then the physician's original goals will be met. However, using this transformed dose as the goal does not allow for the plan to be better than what the physician originally requested, if the anatomical variations are favorable, it simply reproduces a plan as good as what was originally planned, assuming that is physically achievable. To illustrate “favorable anatomical variations”, consider the case where all the OARs move further away from the target. Clearly in this case, it is geometrically much easier to treat the target just as intended (to the same dose level), but deliver less dose to the OARs. A solution would be to apply some logic so that when an OAR or portion of an OAR moves further from the target, the DVF is processed (modified) to constrain the distance to remain constant. Using this processed DVF to transform the dose would result in a goal dose distribution that maintained the same target dose and target conformality, but demonstrated lower doses to those OARs or portions of OARs that in reality were further from the target(s).